The ability to predict, anticipate and reason about future outcomes is a key component of
intelligent decision-making systems. In light of the success of deep learning in computer …

Abstract From CNN, RNN, to ViT, we have witnessed remarkable advancements in video
prediction, incorporating auxiliary inputs, elaborate neural architectures, and sophisticated …

This work introduces double-mapping Gated Recurrent Units (dGRU), an extension of
standard GRUs where the input is considered as a recurrent state. An extra set of logic gates …

We propose a deep neural network for the prediction of future frames in natural video
sequences. To effectively handle complex evolution of pixels in videos, we propose to …

Video prediction is a challenging task due to its nature of uncertainty especially for
forecasting a long period. To model the temporal dynamics advanced methods benefit from …

Studies show lots of advanced research on various data types such as image, speech, and
text using deep learning techniques, but nowadays, research on video processing is also an …

An agent that is capable of predicting what happens next can perform a variety of tasks
through planning with no additional training. Furthermore, such an agent can internally …

In this work we propose a simple unsupervised approach for next frame prediction in video.
Instead of directly predicting the pixels in a frame given past frames, we predict the …

We describe a modular framework for video frame prediction. We refer to it as a Flexible
Spatio-Temporal Network (FSTN) as it allows the extrapolation of a video sequence as well …

Much of recent research has been devoted to video prediction and generation, yet most of
the previous works have demonstrated only limited success in generating videos on short …